Recovering the second moment of the strain distribution from neutron Bragg edge data

Point by point strain scanning is often used to map the residual stress (strain) in engineering materials and components. However, the gauge volume and hence spatial resolution is limited by the beam defining apertures and can be anisotropic for very low and high diffraction (scattering) angles. Alternatively, wavelength resolved neutron transmission imaging has a potential to retrieve information tomographically about residual strain induced within materials through measurement in transmission of Bragg edges - crystallographic fingerprints whose locations and shapes depend on microstructure and strain distribution. In such a case the spatial resolution is determined by the geometrical blurring of the measurement setup and the detector point spread function. Mathematically, reconstruction of strain tensor field is described by the longitudinal ray transform; this transform has a non-trivial null-space, making direct inversion impossible. A combination of the longitudinal ray transform with physical constraints was used to reconstruct strain tensor fields in convex objects. To relax physical constraints and generalise reconstruction, a recently introduced concept of histogram tomography can be employed. Histogram tomography relies on our ability to resolve the distribution of strain in the beam direction, as we discuss in the paper. More specifically, Bragg edge strain tomography requires extraction of the second moment (variance about zero) of the strain distribution which has not yet been demonstrated in practice. In this paper we verify experimentally that the second moment can be reliably measured for a previously well characterised aluminium ring and plug sample. We compare experimental measurements against numerical calculation and further support our conclusions by rigorous uncertainty quantification of the estimated mean and variance of the strain distribution

Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction.

From Europe PMC via Jisc Publications RouterHistory: ppub 2021-10-01, epub 2021-10-21Publication status: PublishedHere we apply hyperspectral bright field imaging to collect computed tomographic images with excellent energy resolution (~ 1 keV), applying it for the first time to map the distribution of stain in a fixed biological sample through its characteristic K-edge. Conventionally, because the photons detected at each pixel are distributed across as many as 200 energy channels, energy-selective images are characterised by low count-rates and poor signal-to-noise ratio. This means high X-ray exposures, long scan times and high doses are required to image unique spectral markers. Here, we achieve high quality energy-dispersive tomograms from low dose, noisy datasets using a dedicated iterative reconstruction algorithm. This exploits the spatial smoothness and inter-channel structural correlation in the spectral domain using two carefully chosen regularisation terms. For a multi-phase phantom, a reduction in scan time of 36 times is demonstrated. Spectral analysis methods including K-edge subtraction and absorption step-size fitting are evaluated for an ex vivo, single (iodine)-stained biological sample, where low chemical concentration and inhomogeneous distribution can affect soft tissue segmentation and visualisation. The reconstruction algorithms are available through the open-source Core Imaging Library. Taken together, these tools offer new capabilities for visualisation and elemental mapping, with promising applications for multiply-stained biological specimens

Crystalline phase discriminating neutron tomography using advanced reconstruction methods

Time-of-flight neutron imaging offers complementary attenuation contrast to X-ray computed tomography (CT), coupled with the ability to extract additional information from the variation in attenuation as a function of neutron energy (time of flight) at every point (voxel) in the image. In particular Bragg edge positions provide crystallographic information and therefore enable the identification of crystalline phases directly. Here we demonstrate Bragg edge tomography with high spatial and spectral resolution. We propose a new iterative tomographic reconstruction method with a tailored regularisation term to achieve high quality reconstruction from low-count data, where conventional filtered back-projection (FBP) fails. The regularisation acts in a separated mode for spatial and spectral dimensions and favours characteristic piece-wise constant and piece-wise smooth behaviour in the respective dimensions. The proposed method is compared against FBP and a state-of-the-art regulariser for multi-channel tomography on a multi-material phantom. The proposed new regulariser which accommodates specific image properties outperforms both conventional and state-of-the-art methods and therefore facilitates Bragg edge fitting at the voxel level. The proposed method requires significantly shorter exposure to retrieve features of interest. This in turn facilitates more efficient usage of expensive neutron beamline time and enables the full utilisation of state-of-the-art high resolution detectors

Core Imaging Library - Part II:multichannel reconstruction for dynamic and spectral tomography

The newly developed core imaging library (CIL) is a flexible plug and play library for tomographic imaging with a specific focus on iterative reconstruction. CIL provides building blocks for tailored regularized reconstruction algorithms and explicitly supports multichannel tomographic data. In the first part of this two-part publication, we introduced the fundamentals of CIL. This paper focuses on applications of CIL for multichannel data, e.g. dynamic and spectral. We formalize different optimization problems for colour processing, dynamic and hyperspectral tomography and demonstrate CIL’s capabilities for designing state-of-the-art reconstruction methods through case studies and code snapshots

A tool for reducing cone-beam artifacts in computed tomography data

Cone-beam computed tomography (CT) with circular scanning trajectory is known to suffer from so called cone-beam artifacts. Cone-beam artifacts are errors in the reconstructed volume due to incomplete radon data. These artifacts increase with increasing distance of the reconstructed plane from the midplane, i.e. the plane containing the X-ray source. Theoretically, the midplane represents the ideal data set for tomographic reconstruction as the entire set of line integrals, i.e. the X-ray attenuation trajectories, are parallel to the plane they are used to reconstruct. The angle between the reconstructed plane and the line integrals used to reconstruct it increases with increasing distance from the midplane. Cone-beam artifacts generally result in a degradation of tomographically reconstructed edges, subsequently affecting dimensional measurements. Appearance of cone-beam artifacts depends on the position and orientation of the object under investigation in the measurement volume. In this paper we propose an algorithm that takes as an input the triangulated surface, e.g. a CAD model, of a scanned object and predicts where the object's surface cannot be reconstructed properly due to cone-beam artifacts. We apply Tuy's data sufficiency condition to define the analytical relationship between each surface triangle in the object model and the ability to reconstruct it using circular scan CT. The output of the proposed algorithm is the object position and orientation that reduces the effects of cone beam artifacts. The proposed algorithm is highly parallelizable and provides computational benefits when compared to conventional CT simulation methods. Operators of CT can use the proposed algorithm to reduce the influence of the cone-beam artifact on the measurements results.status: publishe

Reviewing GPU architectures to build efficient back projection for parallel geometries

status: Published onlin

Evaluating the effects of detector angular misalignments on simulated computed tomography data

The quality of dimensional measurements made by industrial X-ray computed tomography (CT) depends on a variety of influence factors in the measurement process. In this paper, the effects of angular misalignments of a flat-panel detector are investigated. First, a forward projection model is applied to evaluate distortions of the radiographic pixel coordinates assigned to X-ray intensities due to various detector rotation angles. Distortion maps are presented for a set of representative detector rotations and the sensitivity of image distortions to each rotation is discussed. It is shown from a simulation study that detector angular misalignments result in systematic errors of the reconstructed volume. The distortion model is inversely applied to generate correction maps that are used to correct the simulated radiographs from a misaligned detector. A new volume is reconstructed from the corrected radiographs and the new deviations are compared to the uncorrected results. The reduction of observed volumetric errors after radiographic correction validates the efficacy of the radiographic distortion model. Additionally, the output of this study can contribute to the development of a geometrical error model for volumetric measurements made by CT.publisher: Elsevier articletitle: Evaluating the effects of detector angular misalignments on simulated computed tomography data journaltitle: Precision Engineering articlelink: http://dx.doi.org/10.1016/j.precisioneng.2016.03.001 content_type: article copyright: Crown Copyright © 2016 Published by Elsevier Inc. All rights reserved.status: publishe

Software-based compensation of instrument misalignments for X-ray computed tomography dimensional metrology

© 2018 Elsevier Inc. X-ray computed tomography (CT) is an imaging technique that allows the reconstruction of an imaged part in the form of a three-dimensional attenuation map. The CT data acquisition process consists of acquiring X-ray transmission images from multiple perspectives. Analysis of the reconstructed attenuation map can provide dimensional and material information about the measured part(s). Therefore, CT is recognized as a solution for quality control tasks, for example dimensional inspection of complex objects with intricate inner geometries. CT measurements can suffer from various sources of error in the measurement procedure. One such influence is the geometrical alignment of the CT instrument components. Typical tomographic reconstruction algorithms impose strict requirements on the relative position and orientation of the three main components: X-ray source, rotation axis of the sample stage, and X-ray detector. Any discrepancy in the actual CT geometry from the geometry assumed by the reconstruction algorithm will contribute to errors in measurements performed on the reconstructed data. There is currently no standardized or easily implementable method for users to compensate geometrical misalignments of the CT instrument. In many cases, the procedure of mechanical adjustment of CT instrument is time consuming and impractical. In this paper, we show that software-based compensation of deviations in CT instrument geometry is an effective alternative to mechanical adjustment of CT instrument. Through computer simulations, we compare qualitatively and quantitatively two methods to compensate CT instrument misalignment: radiographic re-binning (interpolation) and a modified conventional reconstruction algorithm with embedded misalignment compensation.status: accepte

Characterization of AM Metal Powder with an Industrial Microfocus CT: Potential and Limitations

This study demonstrates that, after adequate scaling error compensation, industrial µ-CT could be a viable metrological technique to derive, with one measurement, primary characteristics of Additive Manufacturing metal powders used in Powder Bed Fusion processes. For distribution and shape analyses, special care must be employed on the ISO value determination prior to surface extraction. The current main limitation relies on the finite focal spot size of the µ-CT X-ray source and consequently on the limited spatial resolution. A local thresholding method has been proposed for surface determination and its statistical validation must be done at different µ-CT scan settings and with different powder specimens. The potential for detecting powder cross-contamination and eventually powder degradation has been introduced and will be the main effort in future studies.More info at: http://aspe.net/technical-meetings/2018-summer-topical-meeting/status: publishe